Source: Journal of Applied Statistics. Unidades: ESALQ, ICMC
Subjects: ANÁLISE DE REGRESSÃO E DE CORRELAÇÃO, COVID-19, DADOS CENSURADOS, MODELOS MATEMÁTICOS, SISTEMA ÚNICO DE SAÚDE
ABNT
HASHIMOTO, Elisabeth Mie et al. The re-parameterized inverse Gaussian regression to model length of stay of COVID-19 patients in the public health care system of Piracicaba, Brazil. Journal of Applied Statistics, v. 50, n. 8, p. 1665-1685, 2023Tradução . . Disponível em: https://doi.org/10.1080/02664763.2022.2036707. Acesso em: 20 ago. 2024.APA
Hashimoto, E. M., Ortega, E. M. M., Cordeiro, G. M., Cancho, V. G., & Silva, I. (2023). The re-parameterized inverse Gaussian regression to model length of stay of COVID-19 patients in the public health care system of Piracicaba, Brazil. Journal of Applied Statistics, 50( 8), 1665-1685. doi:10.1080/02664763.2022.2036707NLM
Hashimoto EM, Ortega EMM, Cordeiro GM, Cancho VG, Silva I. The re-parameterized inverse Gaussian regression to model length of stay of COVID-19 patients in the public health care system of Piracicaba, Brazil [Internet]. Journal of Applied Statistics. 2023 ; 50( 8): 1665-1685.[citado 2024 ago. 20 ] Available from: https://doi.org/10.1080/02664763.2022.2036707Vancouver
Hashimoto EM, Ortega EMM, Cordeiro GM, Cancho VG, Silva I. The re-parameterized inverse Gaussian regression to model length of stay of COVID-19 patients in the public health care system of Piracicaba, Brazil [Internet]. Journal of Applied Statistics. 2023 ; 50( 8): 1665-1685.[citado 2024 ago. 20 ] Available from: https://doi.org/10.1080/02664763.2022.2036707